Global Economic Outlook 2014 and comparing the forecasting performance of international organizations

Transcription

1 Global Economic Outlook 2014 and comparing the forecasting performance of international organizations Pingfan Hong Zhibo Tan ASSA Annual Meeting Philadelphia Pingfan Hong is the Chief of the Global Economic Monitoring Unit of the UN Department of Economic and Social Affairs Zhibo Tan is a Ph.D. candidate in Peking University and co authored part II of this work when he interned at the UN Views expressed here are those of the speakers and they do not necessarily represent the views of the UN

2 PART ONE United Nations World Economic Situation and Prospects 2014 Chapter I: Global Economic Outlook 2

3 Outline for PART ONE Global macroeconomic trends growth prospects inflation and employment international trade and finance Uncertainties and risks QE exit, vulnerability in EM Remaining risks in euro area Policy issues fiscal and monetary policy stance international policy coordination 3

4 Global economy still on a slow and bumpy recovery Forecast made in WESP 2013 Forecast made in WESP

5 De-coupling or re-coupling 5

6 A shift in growth contribution? 6

7 Developed economies: healing slowly in the aftermath of the financial crisis 7

8 Developing countries: backstopping the growth moderation 8

9 Economies in transition: some strengthening 9

10 Unemployment rates elevated 10

11 Inflation remains benign in most part of the world 11

12 World trade growing at a sluggish pace 12

13 Commodity prices 13

14 Increase in external financing costs for emerging markets 14

15 Depreciation of currencies in emerging economies 15

16 Uncertainties and risks Unwinding of the QE A hard landing for emerging economies Remaining fragility in euro area Fiscal policy in the United States Geopolitical risks Environmental disasters 16

17 QE expanded central bank s assets 17

18 Effects of the QE Positive: stabilizing financial markets, bailing-out banks, supporting economic recovery and jobs, good sill-overs to other economies; Negative: market distortion, repressing risk premium, moral hazard for banks, bad spill-overs to emerging economies. 18

19 Risks of the QE exit: riding on a tiger s back Premature and unsmooth exit will lead to: Overshooting of long-term interest rates, shocks to financial markets and real economy, reversing capital inflows to emerging economies, and increasing their external financing costs. Delayed exit will lead to: asset bubbles and inflation 19

20 Overshooting of long-term interest rates 20

21 Risks for a hard landing in emerging economies Vulnerability of emerging economies to external shocks Challenges to overcome structural bottlenecks in their domestic economy 21

22 Vulnerability of emerging economies to external shocks Reversal of capital inflows Current account balance External debt Foreign reserves Exchange rate regimes and macroeconomic policy space 22

23 Current account/gdp: Asian financial crisis V.S. today 23

24 External Debt/GDP: Asian financial crisis V.S. today 24

25 Foreign reserves/gdp: Asian financial crisis V.S. today 25

26 Policy challenges (1) Macroeconomic policy stance more diverse across countries Developed economies: A combination of fiscal tightening and monetary easing Current Japan exception (expansionary fiscal and monetary) Challenge: managing a smooth QE exit 26

27 Policy challenges (2) Developing countries and economies in transition: Reducing vulnerability to a more challenging international economic condition Meeting different needs in the domestic economy Reforms to deal with structural impediments 27

28 Policy challenges (3) International policy coordination: -Focus more on jobs -Mitigate the spill-over effects of QE exit -Manage global imbalances -Ensure sufficient international resources to the LDCs to support the MDGs and post-2015 development agenda 28

29 Global imbalances 29

30 ODA flows declined in past two years 30

31 PART TWO A comparative study of the forecasting performance of three international organizations 31

32 Outline for PART TWO Background information about the forecasts by UN,IMF and World Bank Technical setting Evaluation of the UN forecasts for Comparing the forecasting performance of UN,IMF and the World Bank for : Forecasting errors in global growth Forecasting errors in growth of developed and developing economies Forecasting errors in growth of selected individual countries Explaining the poor forecasting for the Great Recession of 2009 Concluding remarks 32

33 Background information about the forecasts by three international organizations UN: World Economic Situation and Prospects (WESP) Project LINK and the LINK modeling system World Economic Forecasting Model IMF: World Economic Outlook (WEO) World Bank: Global Economic Prospects (GEP) 33

34 Technical setting f t forecast of GDP growth (%) for year t, as projected in t 1 g t GDP growth for year t, as officially reported in year t+1 and t+2 e t =( (100+f t )/(100+ g t ) 1)*100,forecasting error Biasness: (Σ e t )/T Efficiency: corr (e t, e t 1 ) Compare with random walk forecasting Root mean square error Mean absolute error 34

35 Evaluation of UN forecasts(1) Growth of World Gross Product ( ) 35

36 Evaluation of UN forecasts(2) GDP growth of developed countries ( ) 36

37 Evaluation of UN forecasts(3) GDP growth of developing countries ( ) 37

38 Evaluation of UN forecasts(4) Statistics summary world developed countries developing countries model random walk model random walk model random walk Mean p value Median p value Maximum Minimum Standard deviations Skewness Kurtosis Jarque-Bera Probability Number of positive errors Fraction of positive errors serial correlation p value root of mean square errors mean absolute errors mean absolute percentage errors Mean equal test (model VS random walk) p=0.74 p=0.83 p=0.27 Median equal test (model VS random walk) p=0.9 p=0.9 p=0.51 Variance equal test (model VS random walk) p=0.00 p=0.00 p=

39 Comparing the forecasts of UN, IMF and WB (1) Errors in forecasting growth of world gross product ( ) Percentage points corr(un, IMF)=0.93, corr(un,wb)=0.92, corr(ifm,wb)=

40 Comparing the forecasts of UN, IMF and WB (2) Errors in forecasting growth of world gross product Statistics summary UN IMF World Bank model random walk model random walk model random walk Mean p value Median p value Maximum Minimum Standard deviations Skewness Kurtosis Jarque-Bera Probability Number of positive errors Fraction of positive errors serial correlation p value root of mean square errors mean absolute errors mean absolute percentage errors Mean equal test (model VS random walk) p=0.83 p=0.89 p=0.82 Median equal test (model VS random walk) p=1.00 p=1.00 p=1.00 Variance equal test (model VS random walk) p=0.07 p=0.23 p=0.07 Statistics equal test (UN VS IMF) Mean p=0.84 Median p=1.00 Variance p=0.67 Statistics equal test (UN VS World Bank) Mean p=0.98 Median p=0.41 Variance p=0.98 Statistics equal test (IMF VS World Bank) Mean p=0.82 Median p=1.00 Variance p=

41 Comparing the forecasts of UN, IMF and WB (3) Errors in forecasting GDP growth of developed countries ( ) Percentage points 41

42 Comparing the forecasts of UN, IMF and WB (4) Errors in forecasting GDP growth of developed countries Statistics summary UN IMF World Bank model random walk model random walk model random walk Mean p value Median p value Maximum Minimum Standard deviations Jarque-Bera Probability Fraction of positive errors serial correlation p value root of mean square errors mean absolute errors mean absolute percentage errors Mean equal test (model VS random walk) p=0.81 p=0.80 p=0.76 Median equal test (model VS random walk) p=1.00 p=1.00 p=1.00 Variance equal test (model VS random walk) p=0.05 p=0.12 p=0.06 Statistics equal test (UN VS IMF) Mean p=0.94 Median p=0.41 Variance p=0.65 Statistics equal test (UN VS World Bank) Mean p=0.94 Median p=1.00 Variance p=0.89 Statistics equal test (IMF VS World Bank) Mean p=0.99 Median p=0.22 Variance p=

43 Comparing the forecasts of UN, IMF and WB (5) Errors in forecasting GDP growth of developing countries ( ) Percentage points 43

44 Comparing the forecasts of UN, IMF and WB (6) Errors in forecasting GDP growth of developing countries Statistics summary UN IMF World Bank model random walk model random walk model random walk Mean p value Median p value Maximum Minimum Standard deviations Jarque-Bera Probability Fraction of positive errors serial correlation p value root of mean square errors mean absolute errors mean absolute percentage errors Mean equal test (model VS random walk) p=0.92 p=0.93 p=0.53 Median equal test (model VS random walk) p=1.00 p=0.41 p=0.41 Variance equal test (model VS random walk) p=0.22 p=0.48 p=0.16 Statistics equal test (UN VS IMF) Mean p=0.81 Median p=1.00 Variance p=0.93 Statistics equal test (UN VS World Bank) Mean p=0.63 Median p=0.41 Variance p=0.97 Statistics equal test (IMF VS World Bank) Mean p=0.81 Median p=0.41 Variance p=

45 Comparing the forecasts of UN and IMF for selected individual countries (1) Errors in forecasting GDP growth of the U.S. ( ) Percentage points 45

46 Comparing the forecasts of UN and IMF for selected individual countries (2) Errors in forecasting GDP growth of Japan ( ) Percentage points 46

47 Comparing the forecasts of UN and IMF for selected individual countries (3) Errors in forecasting GDP growth of Germany ( ) Percentage points 47

48 Comparing the forecasts of UN and IMF for selected individual countries (4) Errors in forecasting GDP growth of China ( ) Percentage points 48

49 Comparing the forecasts of UN and IMF for selected individual countries (5) Errors in forecasting GDP growth of India ( ) Percentage points 49

50 Comparing the forecasts of UN and IMF for selected individual countries (6) Errors in forecasting GDP growth of Brazil ( ) Percentage points 50

51 Comparing the forecasts of UN and IMF for selected 10 individual countries Statistics summary of errors in forecasting GDP growth UN IMF Mean Mean equal test p value p=0.99 Median Median equal test p value p=0.41 Maximum Variance equal test Minimum p=0.64 Standard deviations Skewness Kurtosis Jarque-Bera Probability Number of positive errors 4 5 Fraction of positive errors Serial correlation p value Root of mean square error Mean absolute error

52 Explaining the failure to predict the Great Recession of 2009 Increased financial complexity, and malodorous practices and chicaneries in high finance in the run up to the financial crisis (securitization, sub prime) Unprecedented acuteness in the damages to financial intermediation when the crisis erupted Extraordinary impact on the real economy (sharp decline investment and consumption) Unparalleled international contagion and transmission (trade and financial flows) Baseline forecasts versus alternative scenarios 52

53 Increased financial complexity and chicanery in high finance in the run up to the global financial crisis Issuance of Subprime Mortgage-Backed Securities, Source: Greenspan (2010) 53

54 Unprecedented acuteness in the damages to financial intermediation when the crisis erupted Sources: IMF World Economic Outlook (2009). 1. Three-month London interbank offered rate minus three-month government bill rate. 2. CDS: credit default swap. 54

55 Extraordinary impact on the real economy (business investment and imports in the U.S. ) Annual change of investment and import (%) I II III I I II III I I II III I I II III I I II III I I II III I I II III I I II III I I II III I I II III I Nonresidential investment Imports Source: Robert Hall (2010) 55

56 Unparalleled international contagion and transmission (international trade and financial flows) 56 Source: IIF

57 Baseline forecasts versus alternative scenarios IMF: WEO for 2009 UN: WESP for 2009 PPP based Exchange rate based Actual growth rate -0.5 Actual growth rate

58 Concluding remarks for PART TWO Forecasts of the three international organizations in the past decade are statistically unbiased, efficient and better than random walk forecasts The forecasting errors of the three organizations are not significantly different, while the UN forecasts are marginally better than the other two in terms of RMSR and MAE All three organizations failed to predict the eruption of the global financial crisis and the Great Recession of The complexity of the financial system, the impact of the financial crisis on the real economy, and the international linkages are the areas for improvement 58